Discovering Efficient Keywords – An Exploratory Study on Comparing the Use of ChatGPT and Other Third-party Tools

Discovering Efficient Keywords – An Exploratory Study on Comparing the Use of ChatGPT and Other Third-party Tools

Contents

Title

Discovering Efficient Keywords – An Exploratory Study on Comparing the Use of ChatGPT and Other Third-party Tools

Author

Pingjun Jiang

Classification JEL

M30, M31, M37.

Abstract

ChatGPT has become a popular keyword discovery tool since it was introduced to the market in late 2022. This study is to compare the effectiveness of this new keyword discovery tool and Spyfu, a widely used third-party tool. The comparison aims to examine which tool is more effective in discovering efficient keywords. The keyword efficiency scores are defined and calculated by using the Data Envelopment Analysis (DEA) based on historical data from a specific period of time. Both ChatGPT and a third-party tool (Spyfu) provide two lists of top keywords with Broad Match and Modified Broad Match. It is found that about forty percent of Spyfu recommended keywords turn out to be efficient, while less than twenty percent of the keywords generated by ChatGPT are efficient. The results of the study indicate that ChatGPT is not as effective in discovering efficient keywords compared to Spyfu. However, ChatGPT is found to be highly effective in predicting search trends and identifying long-tail keywords and query questions that are specific and targeted to the users’ needs. A combination of both tools may provide the best results for keyword discovery and strategy fine-tuning.

Keywords

Data Envelopment Analysis (DEA), Keyword Efficiency, ChatGPT, Search Engine Marketing.

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